It is often desirable to measure the abundance or relative concentration of biological analytes. Such analytes include, for example, chromosomes, genome sequences, mRNAs, peptides, compounds, genotypes, or haplotypes. Experimental techniques for making such measurements may introduce biases, which if unaccounted for can artificial skew results.
A drawback of existing methods is that they frequently fail to account for inter experiment or batch variability caused by differing coverage of assay elements between experiments, experiments, or runs. Differing samplings of such assay elements are the result of chance or systemic factors such as environment, differing experimental application, or other factors. For example, in the case of measuring chromosome abundance, the GC content of sampled nucleic acid sequences of different chromosomes may bias chromosome abundance measurements suggesting an aberration in chromosome abundance even when no real change in chromosome abundance has occurred. (GC content is the percentage or ratio of guanine and cytosine in all nitrogenous bases in a nucleic acid.)
For these reasons, improved techniques for addressing experimental variability in biological assays are desirable.